Viewers oftentimes use video cassette recorders (VCRs) and digital video recorders (DVRs) to record television, cable, and satellite video broadcasts for later viewing. Such broadcasts typically include segments of program content separated by blocks of one or more consecutive segments of commercial content (e.g., non-program content, such as advertising, station identification, previews, and the like).
Viewers typically prefer to watch consecutive segments of program content continuously without interruption by any intervening segments of commercial content. To this end, various technologies have been developed to enable viewers to skip over commercial content in broadcast video. For example, VCRs and DVRs typically include fast forward functionality that allows viewers to advance quickly through commercial content in recorded broadcast video data. In addition, recently developed VCRs and DVRs include automatic commercial detection technology that is able to distinguish commercial content from program content based on audiovisual features of the broadcast video.
At least in the United States, each segment of commercial content typically is bounded by one or more black video frames and accompanying periods of silence. As a result, many automatic commercial detection approaches rely at least in part on the detection of black video frames, either alone or in combination with accompanying silence, to detect the boundaries of each individual commercial segment. Some automatic commercial detection approaches additionally include functionality for confirming whether a commercial has occurred based on an analysis of the video data. In one such automatic commercial detection system, candidate commercial segments are identified based on the detection of a black video frame and an analysis of frame cut parameters that are derived from the video data. This system then relies on one or more of logo detection, commercial signature detection, brand name detection, detection of similar features located within a specified period of time before a frame being analyzed, and character detection to confirm that each of the identified candidate commercial segments does indeed correspond to a commercial segment.
These prior automatic commercial detection approaches implicitly assume that black frame detection, either alone or in combination with silence detection, can accurately detect the boundaries between commercial content and program content. Oftentimes, however, it is very difficult to detect each black frame and each silent period with high accuracy. Such difficulty is increased when broadcasters actively seek to thwart the ability of automatic commercial detection systems to detect the transitions between commercial content and video content. For example, broadcasters in some countries are replacing the black video frames at the boundaries of commercial segments with frames of a uniform non-black color, such as blue or white. As a result, prior automatic commercial detection systems tend to produce imperfect commercial segmentation results. Depending on the viewer, such results may be sufficiently unsatisfactory (e.g., when the end of a program is labeled incorrectly as commercial content and therefore not recorded) that they may abandon the use of such technology.
What are needed are systems and methods that are capable of detecting the boundaries of commercial content and program content in video data with high accuracy.